(1) Field of the Invention
The present invention relates to a system and method for learning and controlling an air/fuel mixture ratio for an internal combustion engine and, more particularly, relates to the system and method therefor in which a supply quantity of fuel to the engine is corrected so that an actual air/fuel mixture ratio sucked into the engine coincides with a target air/fuel mixture ratio.
(2) Description of the Background Art
Japanese Patent Application First Publications No. showa 60-90944 published on May 22, 1985 and No. Showa 61-190142 published on Aug. 23, 1986 exemplify electronically controlled fuel injection systems with air/fuel mixture ratio feedback correction controlling functions in which the air/fuel mixture ratio is learned and controlled.
The correction control of the air/fuel mixture ratio is such that an oxygen concentration sensor installed in an engine exhaust system is used to determine a rich or lean state of the actual air/fuel mixture ratio with respect to a target air/fuel mixture ratio (for example, a stoichiometric air/fuel mixture ratio) and an air/fuel mixture ratio feedback correction coefficient LMD used to correct a fuel injection quantity is set on a basis of the result of determination of the rich or lean state of the actual air/fuel mixture ratio at a proportion-and-integration control. A basic fuel injection quantity Tp calculated from a parameter of the engine driving condition related to an intake air quantity sucked into the engine (for example, sucked (intake) air quantity Q and engine revolution speed N) is corrected with the air/fuel mixture ratio feedback correction coefficient LMD so that the actual air/fuel mixture ratio is coincident with the target air/fuel mixture ratio.
Then, a deviation of the actual air/fuel mixture ratio feedback correction coefficient LMD from a reference value (a target or finally converged value) is learned for each of a plurality of previously defined engine driving regions (or driving area) so as to define a learning correction coefficient KBLRC (learning correction value of the air/fuel mixture ratio). The basic fuel injection quantity Tp is corrected with the learning correction coefficient KBLRC so that a basic air/fuel mixture ratio derived without the correction coefficient LMD is controlled so as to substantially match with the target (stoichiometric) air/fuel mixture ratio. In addition, during the execution of the air/fuel mixture ratio feedback control, the basic air/fuel mixture ratio is further corrected with the correction coefficient LMD to calculate a final fuel injection quantity Ti.
Consequently, a fuel supply correction corresponding to a different correction request which is different for each engine driving condition can be carried out.
Then, the air/fuel mixture ratio feedback correction coefficient LMD can become stable in the vicinity to the reference value so that an air/fuel mixture ratio controllability can be improved.
On the other hand, since the air/fuel mixture ratio learning correction coefficient KBLRC is set to cope with the different air/fuel mixture ratio correction request generated according to the different driving conditions as described above, it is desirable to learn the learning correction coefficient KBLRC with the engine driving regions divided as close as possible.
However, if the whole driving region is closely divided into the plurality of the engine driving regions and the learning correction coefficient KBLRC for each engine driving region is learned, an opportunity of learning is reduced at each driving region and a convergence characteristic of the learning is worsened. Then, since any one of the regions in which the learning is carried out and any other regions in which no learning is carried out are mixed in the whole driving region, a large stepwise difference in the air/fuel mixture ratio between the respective driving regions occurs.
A Japanese Patent Application First Publication No. Heisei 3-145539 published on Jun. 20, 1991 exemplifies a previously proposed air/fuel mixture ratio learning and controlling system in which a plurality of learning maps are installed in which the number of divisions of the engine driving regions are different from each other, the learning of the learning correction coefficient KBLRC is started from one of the learning maps in which the number of divisions of the driving regions is less than the others and the driving region for a unit of learning is wider from among the learning maps and the learning is transferred to one of the learning maps in which the number of divisions are greater than the others and the driving region for the unit of learning is narrower as the learning is advanced.
In the air/fuel mixture ratio learning according to the disclosed air/fuel mixture ratio learning and controlling system, the favorable learning convergence characteristic can be secured by learning the learning correction coefficient KBLRC for each unit of engine driving region at the initial state of learning and the air/fuel mixture ratio learning is carried out for the closer engine driving region as the learning is advanced, the accurate learning of the air/fuel mixture ratio can be carried out so as to cope with the different correction request for the different engine driving condition.
However, in the latter previously proposed air/fuel mixture ratio learning and controlling system described above, the plurality of learning maps are installed which store the air/fuel mixture ratio learning correction values for the respective engine driving regions. Therefore, a large capacity of memories is required.
In addition, since the learning correction values are learned as representative values in the respectively divided driving regions, it is inevitable to change stepwise the learning correction values when the driving regions on the learning maps are switched and the stepwise changes in the learning correction values generate variations in the air/fuel mixture ratio.
In details, although the errors in the basic air/fuel mixture ratio are generated due to various causes, the basic air/fuel mixture ratio is not varied stepwise for the change in the driving conditions and the request for the air/fuel mixture ratio learning correction value is inherently not varied stepwise.
However, since, as described above, the air/fuel mixture ratio learning correction values as the representative correction levels in the driving regions having a certain magnitude are learned, the stepwise change in the learning correction value which does not correspond to the change in the actual driving condition when the change in the driving condition which crosses the boundaries of the driving regions. Although the change width of the stepwise learning correction values can be reduced when the learning driving region is narrowed, it is not practical to divide the driving regions as close as possible in the case where the learning is such as to gradually narrow the learning region. It is inevitable to generate the stepwise difference in correction levels from among the regions on the learning maps.